TY - GEN
T1 - Scalable inference of overlapping communities
AU - Gopalan, Prem
AU - Mimno, David
AU - Gerrish, Sean M.
AU - Freedman, Michael J.
AU - Blei, David M.
PY - 2012
Y1 - 2012
N2 - We develop a scalable algorithm for posterior inference of overlapping communities in large networks. Our algorithm is based on stochastic variational inference in the mixed-membership stochastic blockmodel (MMSB). It naturally interleaves subsampling the network with estimating its community structure. We apply our algorithm on ten large, real-world networks with up to 60,000 nodes. It converges several orders of magnitude faster than the state-of-the-art algorithm for MMSB, finds hundreds of communities in large real-world networks, and detects the true communities in 280 benchmark networks with equal or better accuracy compared to other scalable algorithms.
AB - We develop a scalable algorithm for posterior inference of overlapping communities in large networks. Our algorithm is based on stochastic variational inference in the mixed-membership stochastic blockmodel (MMSB). It naturally interleaves subsampling the network with estimating its community structure. We apply our algorithm on ten large, real-world networks with up to 60,000 nodes. It converges several orders of magnitude faster than the state-of-the-art algorithm for MMSB, finds hundreds of communities in large real-world networks, and detects the true communities in 280 benchmark networks with equal or better accuracy compared to other scalable algorithms.
UR - http://www.scopus.com/inward/record.url?scp=84877735139&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84877735139&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84877735139
SN - 9781627480031
T3 - Advances in Neural Information Processing Systems
SP - 2249
EP - 2257
BT - Advances in Neural Information Processing Systems 25
T2 - 26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012
Y2 - 3 December 2012 through 6 December 2012
ER -